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Microbial eukaryotes in the Movile Cave chemosynthetic ecosystem
1. Methods
Results
Resume
Microbial eukaryotes in the Movile Cave chemosynthetic ecosystem
1 Ecologie Systématique Evolution, Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Orsay, France ; 2 Group for underwater and speleological exploration, Emil Racovita Institute of Speleology, Bucharest, Romania ; * Corresponding author: puri.lopez@u-psud.fr
Prospects Literature references John St. John, https://github.com/jstjohn/SeqPrep
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10–12 (2011).
Rognes, T., Flouri, T., Nichols, B., Quince, C. & Mahé, F. VSEARCH: a versatile open source tool for metagenomics. PeerJ Prepr. 4, e2409v1 (2016).
Mahé, F., Rognes, T., Quince, C., De Vargas, C. & Dunthorn, M. Swarm v2: highly-scalable and high-resolution amplicon clustering. PeerJ 3, e1420 (2015).
Fu, L., Niu, B., Zhu, Z., Wu, S. & Li, W. CD-HIT: Accelerated for clustering the next-generation sequencing data. Bioinformatics 28, 3150–3152 (2012).
Guillou, L. et al. The Protist Ribosomal Reference database (PR2): A catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated
taxonomy. Nucleic Acids Res. 41, D597-604 (2013).
Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).
Forti, P., Galdenzi, S. & Sarbu, S. M. The hypogenic caves: A powerful tool for the study of seeps and their environmental effects. in Continental Shelf
Research 22, 2373–2386 (2002).
Ø Consolidation of the metabarcoding method and analyses of the results (divergent OTUs)
Ø Metatranscriptomic approach (Implementation, Phylogenomics and Activities analyses)
Ø Share worldwide our results by publishing
Reboul G. 1, Hillebrand-Voiculescu A.M. 2, Bertolino, P. 1, Moreira D. 1, López-García P. *,1
Metabarcoding approach
Forward
primer
Reverse
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18 S V4-V5 regionsMID MID
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Reverse
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18 S V4-V5 regionsMID MID
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18 S V4-V5 regionsMID MID
Forward
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18 S V4-V5 regionsMID MID
Forward
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18 S V4-V5 regionsMID MID
Forward
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18 S V4-V5 regionsMID MID
Forward
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18 S V4-V5 regionsMID MID
Forward
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Reverse
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18 S V4-V5 regionsMID MID
Forward
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Reverse
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18 S V4-V5 regionsMID MID
Forward
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18 S V4-V5 regionsMID MID
Forward
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18 S V4-V5 regionsMID MID
Forward
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18 S V4-V5 regionsMID MID
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18 S V4-V5 regionsMID MID
Forward
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18 S V4-V5 regionsMID MID
Forward
primer
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18 S V4-V5 regionsMID MID
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
Trimming primers and MIDs - Removing bad quality bases - Discarding too short sequences (cutadapt)
Reverse
primer
part of 18 S V4-V5
regions
MID
part of 18 S V4-V5
regions
MID Forward
primer
Reverse
primer
part of 18 S V4-V5
regions
MID
part of 18 S V4-V5
regions
MID Forward
primer
Reverse
primer
part of 18 S V4-V5
regions
MID
part of 18 S V4-V5
regions
MID Forward
primer
Merging paired-end reads (flash)
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions
18 S V4-V5 regions 18 S V4-V5 regions 18 S V4-V5 regions 18 S V4-V5 regionsx1 x1 x2 x1
Dereplicating the good sequences (vsearch)
18 S V4-V5 regions 18 S V4-V5 regions 18 S V4-V5 regions 18 S V4-V5 regions x1x1x1x1
Clustering sequences in OTUs (Swarm, cd-hit-est)
18 S V4-V5 regions 18 S V4-V5 regions 18 S V4-V5 regions 18 S V4-V5 regions x2x3x3x1
OTU1 OTU2 OTU3 OTU4
Taxonomic assignation (BlastN against PR2 and Silva databases)
Aggregating good sequences
18 S V4-V5 regions 18 S V4-V5 regions 18 S V4-V5 regions 18 S V4-V5 regions x2x3x3x1
OTU1 OTU2 OTU3 OTU4
taxa1 taxa2 unknown taxa3
Selecting OTUs
18 S V4-V5 regions 18 S V4-V5 regions 18 S V4-V5 regions 18 S V4-V5 regions x2x3x3x1
OTU1 OTU2 OTU3 OTU4
taxa1 taxa2 unknown taxa3
OTU2 OTU3 OTU4Abundance
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Relative abundance analyses using arbitrary criteria
(here single read OTUs are discarded)
Sample 1 Sample 2 Sample 3
Alveolata Opisthokonta Stramenopiles
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
tot_reads
rank1
Alveolata Amoebozoa Archaeplastida Excavata Opisthokonta Rhizaria Stramenopiles
Ciliophora
Choanoflagellida
Fungi
Ochrophyta Stramenopiles_X
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
tot_reads
rank2
Ciliophora Conosa Chlorophyta Streptophyta Metamonada Choanoflagellida
Fungi Mesomycetozoa Cercozoa Ochrophyta Stramenopiles_X
Alveolata
Archaeplastida
Hacrobia
Opisthokonta Rhizaria Stramenopiles
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
tot_reads
rank1
Alveolata Amoebozoa Apusozoa Archaeplastida Excavata Hacrobia Opisthokonta Rhizaria Stramenopiles
Apicomplexa
Ciliophora
Dinophyta
Perkinsea
Chlorophyta
Fungi
Cercozoa
Radiolaria
Ochrophyta
Stramenopiles_X
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
tot_reads
rank2
Apicomplexa Ciliophora Dinophyta Perkinsea Breviatea
Apusomonadidae Chlorophyta Streptophyta Metamonada Haptophyta
Katablepharidophyta Telonemia Choanoflagellida Fungi Metazoa
Cercozoa Radiolaria Ochrophyta Stramenopiles_X
CDhit OTUs
8,488 142,371
OTUs > 1 read
301 134,184
multiple samples
37 113,883
bh_cov > 70
bh_ident_score>80
34 106,386
bh_cov > 80
bh_ident_score>80
33 105,852
bh_cov > 90
bh_ident_score>80
30 88,418
OTUs in only one
sample
264 20,301
bh_cov > 80
bh_ident_score>80
238 18,885
bh_cov > 80
bh_ident_score>90
215 17,849
bh_cov > 90
bh_ident_score>80
207 4,793
bh_cov > 90
bh_ident_score>90
197 4,769
Acknowledgements Ø COST Action TD1308 “ORIGINS” and ERC “ProtistWorld” for funding
Ø DEEM team for the nice working atmosphere
Results using OTUs identified in at least one sample Results using OTUs identified in only one sample
8,488 142,371
nb OTUs nb reads
Legend
bh_cov: blast hit coverage
bh_ident_score: blast hit identity score
Multiplexed Illumina Mi-Seq
paired-end sequencing
Conclusions
A small number of OTUs (34) but a high number of reads (106,386) are shared by the 3 samples.
This means that there is a low microbial eukaryote diversity in the Movile Cave.
Also, Alveolata and Stramenopiles seem to be the most abundant protist superphyla in the Movile Cave.
Movile cave organization (Forti et al. 2002)
Movile cave in the world (google maps)
Microbial eukaryotes
Metazoa
Procaryotes
HAS BEEN
STUDIED
HAS BEEN
STUDIED
OUR PROJECT
Protist diversityMetabarcoding 18S analyses
Phylogenomic analysesMetatranscriptomic analyses
Sequencing and Bioinformatic approaches, methods, pipelines and analyses
A high number of OTUs (197) are found in only one sample but a small number of reads (4,769).
This means that there are minor divergent species in the Movile Cave depending on the environment (plankton, floating mats).
Rhizaria (mostly Cercozoa) is the most abundant protist superphylum in the Movile Cave according to our results.
Also, noted the presence of Apusozoa and Hacrobia superphyla not present in the multiple sample analyses (to investigate).
Multiple parameter combinations were tested in order
to choose the best couple of criteria for our analyses
Sample 1 Sample 2 Sample 3
Suboxic biofilm
• floating mat
• fixed in EtOH
Suboxic biofilm
• live mat
• 2 months at room
T° in the dark
Plankton
• all water filtered
• 0.2-200 µm
fraction retained
DNA Extraction, sample preparation for sequencing
Legend
: tag to remember from which
sample comes from the read
: tag to select or discard an OTU
for the downstream analyses
Movile cave floating mat
Microbial eukaryotes (Protists)